This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Age related changes in the function and structure of the tears producing lacrimal gland is postulated to be contributed by progressive reduction in parasympathetic innervation. The goal is to identify affected genes that are found in common in aging and experimental denervated dry eye model, and to elucidate cellular networks that are altered with age and those that displayed neural-specific regulation. We have found increased expression of cartilage derived-retinoic acid-sensitive protein, also known as melanoma inhibitory activity (MIA) protein with age. Increased expression of MIA has been found in serum and synovial fluid in patients with osteoarthritis and rheumatoid arthritis. Two related members of the MIA family, MIA2 and MIA3, were also examined, and only MIA2 were found expressed and increased in aged lacrimal gland. Immunohistochemical analysis found MIA localized predominantly to intralobular ducts, with sparse staining in acini. To investigate the neural control of MIA expression in the lacrimal gland, we carried out parasympathetic and sympathetic denervation. Real-time RT-PCR, western blot analysis, and immunohistochemical analysis did not reveal significant differences between the controls and denervated in the 4 months or 24 months group. Since members of the MIA family may be one of many factors associated with the altered immune condition in the lacrimal gland, proinflammatory genes that were found enriched in aged and denervated lacrimal glands from microarray results were also selected and analyzed by real time RT-PCR analysis. The MetaCore systems biology platform was used to identify common and unique proinflammatory genes under different neural conditions, as well as those genes that displayed gender-specific expression. Using these results, we generated a regulatory network in the context of MIA and MIA2, and consist of, among others, caspase 1, interleukin-1 beta, transforming growth factor beta -1, intercellular adhesion molecule-1, vascular adhesion molecules-1, and annexin (A1, A3, A5). Sub-networks of expression data and sub-networks of transcription regulation were generated based on a priori knowledge and interpreted using gene ontology enrichment.